Alcohol and brain structure across the lifespan: A systematic review of large‐scale neuroimaging studies

Abstract Alcohol exposure affects brain structure, but the extent to which its effects differ across development remains unclear. Several countries are considering changes to recommended guidelines for alcohol consumption, so high‐quality evidence is needed. Many studies have been conducted among small samples, but recent efforts have been made to acquire large samples to characterize alcohol's effects on the brain on a population level. Several large‐scale consortia have acquired such samples, but this evidence has not been synthesized across the lifespan. We conducted a systematic review of large‐scale neuroimaging studies examining effects of alcohol exposure on brain structure at multiple developmental stages. We included studies with an alcohol‐exposed sample of at least N = 100 from the following consortia: ABCD, ENIGMA, NCANDA, IMAGEN, Framingham Offspring Study, HCP and UK BioBank. Twenty‐seven studies were included, examining prenatal (N = 1), adolescent (N = 9), low‐to‐moderate‐level adult (N = 11) and heavy adult (N = 7) exposure. Prenatal exposure was associated with greater brain volume at ages 9–10, but contemporaneous alcohol consumption during adolescence and adulthood was associated with smaller volume/thickness. Both low‐to‐moderate consumption and heavy consumption were characterized by smaller volume and thickness in frontal, temporal and parietal regions, and reductions in insula, cingulate and subcortical structures. Adolescent consumption had similar effects, with less consistent evidence for smaller cingulate, insula and subcortical volume. In sum, prenatal exposure was associated with larger volume, while adolescent and adult alcohol exposure was associated with smaller volume and thickness, suggesting that regional patterns of effects of alcohol are similar in adolescence and adulthood.


| INTRODUCTION
Heavy alcohol consumption is a leading cause of death and disease worldwide, leading to increased rates of cancer, liver disease and risk for accidents. 1,2Alcohol exposure can begin as early as conception, and alcohol consumption is common throughout the lifespan; in the United States, 86% and 82% of men and women, respectively, report alcohol use at some point in their lifetimes. 3The mean age of initiation of alcohol use is 17, 4 when the brain is still developing.A typical developmental course of brain structure involves increases in grey matter volume and density throughout the brain before puberty, followed by a rapid decline during and after puberty. 5Grey matter volume loss continues more slowly during middle age before accelerating in older adults. 6Alcohol is thought to affect brain structure primarily through directly causing neuronal death.Neuronal death related to alcohol use can be caused by acetaldehyde exposure, 7 oxidative stress, 8 decreases in glucose metabolism following acute alcohol intake, 9 and liver damage, as toxins that are normally processed and removed by the liver can build up and enter the brain. 10Heavy alcohol exposure can also reduce the number of stem cells that help to generate new neurons. 8Despite evidence that alcohol exposure at any time can affect brain structure, it remains unclear to what extent the age at which individuals consume alcohol determines its effects on brain structure.
The most common method to study alcohol's effect on brain structure is magnetic resonance imaging (MRI), and recent evidence suggests that large sample sizes are necessary to provide reliable estimates of relationships between brain structure and function. 11Given the recent attention to guidelines for healthy alcohol consumption, and efforts by some countries to modify guidance, 12 it is important to have high quality evidence about the effects of alcohol on the brain across developmental stages.Many previous studies examining alcohol's effects on brain structure have included modest samples sizes (e.g., <50 participants per group).4][15][16][17][18][19] These efforts often examine different development periods, such as adolescence, young adulthood, or middle and later adulthood.However, to date, no systematic review has synthesized these large-scale studies to describe how alcohol affects brain structure across the lifespan.
This review leverages data from large-scale consortium studies to examine the effects of alcohol exposure and consumption on brain volume across developmental periods.Specifically, we examined prenatal alcohol exposure and alcohol use in adolescence and adulthood, with adult studies divided by amount of alcohol consumption (i.e., low-to-moderate exposure and heavy exposure).To ensure that studies were sufficiently powered to detect brain-wide associations 11 and to covary for important potential confounding factors such as age, sex, health history, socioeconomic status and other substance use,  S1 for a description of each consortium).We hypothesized that alcohol exposure would be associated with similar patterns of smaller brain volumes (relative to controls) across all developmental stages.We also evaluated whether the effects of alcohol differed by sex.

This review follows the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) guidelines. 20The protocol was pre-registered through the Open Science Framework (OSF, protocol can be accessed at https://osf.io/hfsu3,currently embargoed) on 1 August 2023.The last search date took place 19 June 2023.Note that the search strategy covered four separate 'concepts':

| Search strategy
(1) alcohol-related terms, (2) brain-related terms, (3) neuroimagingrelated terms and (4) the names or grant numbers of the seven consortia included in the review.The final search combined 1 AND 2 AND 3 AND 4.

| Eligibility criteria and article screening process
Results of the search procedure described above were uploaded into Covidence, which automatically removed duplicates and generated 404 distinct articles to screen.Covidence was used for management of all steps of the review/screening and data extraction process.First, title and abstract screening was conducted for the 404 articles.Two reviewers independently reviewed each title and abstract, and conflicts were resolved via full group consensus from all authors.Included articles were required to be (1) peer-reviewed, (2) available in English, (3) empirical studies that analysed alcohol use/exposure in relation to brain structural changes and (4) to have used MRI to assess brain structure (i.e., volume, thickness and area).Reviews, reports, metaanalyses, dissertations, theses, book chapters, abstracts, case studies, guidelines, expert opinions, commentaries and other non-peer reviewed work were excluded.
More detail on inclusion/exclusion criteria applied are listed in Table 2. Regarding the inclusion criterion that required articles to have an alcohol-exposed sample of at least n = 100, meta-analyses comparing brain volume between heavy drinkers and light drinkers suggest the greatest differences between these groups in regional brain volume represent large effect sizes (i.e., Cohen's d > 1.0). 21,22Assuming the average difference in brain volume between these groups represents a medium effect size (d = 0.5), a group sample size of 105 would provide 95% power to detect such an effect.Thus, a sample size of n > 100 per group should provide adequate power to detect effects of alcohol in brain regions with clinically meaningful effects 23 and allow for adjustment of covariates that could confound results, such as age, sex, socioeconomic status and co-occurring substance use.
Fifty-eight articles passed title and abstract screening and underwent full-text review.Two reviewers independently reviewed each text, and conflicts were resolved by an independent third reviewer.
Twenty-seven articles passed full-text screening and underwent data extraction for inclusion in this review.3.

| Quality assessment
The NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was used.Articles were rated on 14 items.The 14 items are listed for reference in the supporting information.
Items cover quality domains such as statistical rigour, study design and transparency of methods.Following recommended guidance for this tool, 1 point was assigned for each 'Yes' answer and 0 points were assigned for each 'No', 'Cannot Determine' or 'Not Reported' answer.If an item was categorized as N/A, this was not counted against the total score.Scoring was conducted by calculating the total score (i.e., number of 'Yes' answers) divided by either 14 or, if any items were rated as N/A, that item was subtracted from the denominator.For example, if two items were rated N/A for a given article, the denominator for that article was 12. Based on these calculations, articles could be rated as 'Poor' (≤34% 'Yes'), 'Fair' (35-63.9%)or 'Good' (≥64%).The final scoring system was adapted from a scoring system used previously. 24

| RESULTS
Our search revealed 640 references matching our criteria across the three databases.After removing duplicates, 404 studies were left for screening.After screening abstracts, 346 studies were excluded, leaving 58 for full-text review.At this stage, 31 studies were excluded, leaving 27 for extraction, which examined prenatal (n = 1), adolescent (n = 9), low-to-moderate adult (n = 11) and heavy adult (n = 7) alcohol exposure.Note that this total is 28, as one study 25  for adults, we divided this phase into studies examining low and moderate exposure versus those examining heavy exposure.Each consortium had its own specific drinking definitions (see Table S1), which corresponded with our 4 broad categories (prenatal, adolescent exposure, low-moderate adult exposure and heavy adult exposure).In general, the adult heavy exposure studies primarily considered samples with alcohol use disorder (AUD) or binge drinking (defined as four or more drinks for women and five or more drinks for men in a single day).The adult low-to-moderate exposure studies considered a broader range of drinking patterns (e.g., ranging from monthly to weekly drinking, and considering up to approximately 7-8 drinks per week as light drinking, and approximately 14-15 drinks per week in the moderate range; see Table S1).The adolescent studies (from IMA-GEN and NCANDA) defined drinking either by AUDIT scores (hazardous drinking defined by an AUDIT score or 8 or greater vs. nonhazardous drinking), or used modified Cahalan criteria, 26 which take into account both frequency and consumption (see Table S1).The summary of findings is presented in Table 4, and greater detail is provided in Table S2.

| Quality assessment
Twenty six of the studies were scored as 'good' quality, and one was scored as 'fair' with a score of 7/12 (8/12 was required for a 'good' rating).Thus, these studies can generally be considered high quality (see Table 3).

| Prenatal alcohol exposure
One study examined prenatal exposure using data from the ABCD sample acquired when the participants were 9-10 years old.Children who were exposed in utero to varying amounts of alcohol (1-90 total drinks over the course of pregnancy), relative to those not exposed, had greater total cerebral volume and greater surface area in the occipital, parietal and temporal lobes. 27In this study, greater total number of maternal drinks during pregnancy was associated with greater total cerebral volume . 27

| Early adolescent alcohol consumption
The studies examining adolescent alcohol exposure and brain structure primarily used the NCANDA sample, [28][29][30][31][32][33][34] but two studies used the IMAGEN 25,35 dataset.These studies generally compared adolescents with low or no alcohol use to those with moderate or heavy  • Meta-analysis • Systematic Review use.Some studies reported on global effects of alcohol consumption on brain structure and found that adolescents who reported greater levels of alcohol use showed smaller total grey matter volume and thickness than those with no/low use. 25,32,33olescents who reported greater levels of alcohol use also showed smaller volume in the prefrontal cortex, 35 frontal lobe, 32,33 temporal cortex 35 and parietal and temporal lobes, but not in the occipital lobe. 32,33Several studies also reported on effects of alcohol in smaller parcels of the brain.Three studies found smaller volume and thickness in parcellations across the frontal lobe, including the middle frontal, superior frontal and inferior frontal gyri. 28,29,34ey also reported smaller volume in the orbitofrontal cortex and precentral gyrus.In the parietal lobe, adolescents who had initiated heavier alcohol use showed smaller volume in the inferior parietal lobe, the precuneus and the postcentral gyrus. 29In the temporal lobe, one study reported similar thickness in adolescents who did or did not drink more alcohol in the inferior, middle and superior temporal gyri, 34 but another paper showed smaller volume in these regions among heavier drinkers. 29Similarly, evidence suggested similar thickness in parcels of the occipital lobe 34 but smaller volume in these parcels in adolescents with greater levels of alcohol use. 29Generally, alcohol use seemed to be associated with smaller volumes across the cortex in adolescents who report heavier alcohol use.
The effects of alcohol were mixed for the cingulate and insula, with some studies reporting greater volume or thickness in participants with heavier alcohol use in the insula, 33 some reporting no difference in the anterior cingulate 34 and insula 32 and some reporting smaller volume in adolescents with heavier patterns of alcohol use in the insula 29 and cingulate. 29,33Greater alcohol exposure was associated with smaller hippocampal and amygdala volume. 30Few papers reported on the striatum.Greater alcohol exposure was associated with smaller total cerebellum volume. 31Among adolescents, subcortical volumes often demonstrated inconsistent effects (e.g., insula and hippocampus) 30,32 or were not reported (e.g., striatum).We suspect the inconsistencies may be due to adolescent alcohol exposure being highly variable and/or due to brain changes across development.
F I G U R E 1 Prisma flow chart depicting the flow of identification and screening of studies for inclusion in this review.

| Low-to-moderate alcohol consumption in adulthood
0][41][42][43][44][45][46] Unlike adolescent or heavy alcohol use studies that had an exposure and a comparison group, these studies generally had more than two groups, reflecting consumption patterns such as abstinence, low use (i.e., 0-7 standard drinks per week), moderate use, and heavier use.They often reported effects on total brain volume, and almost all indicated that, controlling for covariates such as sex, age, ethnicity, socioeconomic status and other substance use, greater alcohol consumption was associated with smaller brain volume. 36,38,39,43,45,46Studies examining smaller parcellations of the brain reported that greater levels of alcohol use were associated with smaller volume and thickness in areas of the frontal, parietal, temporal and occipital lobes. 37,45,465][46] These studies nearly unanimously reported that greater alcohol consumption was associated with smaller volume across nearly all brain regions.

| Heavy alcohol consumption in adulthood
The studies examining heavy alcohol consumption (i.e., meeting criteria for alcohol use disorder or for binge drinking) in adulthood came from the ENIGMA consortium 25,[47][48][49][50][51] and the HCP dataset. 52 ≈ volume 45 # volume 39,41 # volume [47][48][49][50][51][52] Striatum Caudate, putamen # volume 39 # volume [47][48][49]51 Nucleus accumbens # volume 41 ≈ volume 48 # volum 47,49,51 Pallidum " volume 39 ≈ volume 47,51 # volume 48 Thalamus, ventral diencephalon " volume 27 # volume 45,46 # volume [47][48][49]51 40 reported widespread smaller volumes associated with greater alcohol consumption, but they applied a stringent correction for multiple comparisons (q < 1.72EÀ4), and these regions did not survive correction.For completeness, we report the regions they list as showing a relationship, given that their correction is more conservative than the typical paper in this literature. d Pfefferbaum et al. 33 reat participants whose drinking exceeded recommended drinking criteria had smaller total temporal volumes than a no/low drinking comparison group but that a greater lifetime number of drinks was associated with larger volume. e hillips et al. 30 reported greater drinking was associated with smaller total hippocampal volume and volume of one hippocampal subfield but with larger volume of two other hippocampal subfields.
f Rossetti et al. 48reported that participants with AUD had smaller cerebellar volume than controls but among those with AUD, a greater number of monthly standard drinks was associated with larger volume.
and some of the ENIGMA samples included younger adults.Some studies reported on global metrics of brain structure and found smaller grey matter volume [48][49][50] and thickness 25 across the cortex in the AUD group relative to the comparison sample.Individuals with AUD, relative to controls, showed less thickness in the middle and superior frontal gyrus, the orbitofrontal cortex and the precentral gyrus. 49In the parietal lobe, individuals with AUD, relative to controls, showed less thickness in the superior parietal lobule, the precuneus and the supramarginal gyrus. 49In the temporal lobe, individuals with AUD showed smaller volume and thickness in the superior temporal gyrus and less thickness in the inferior temporal gyrus, temporal pole and parahippocampal gyrus. 47,49,52In the occipital lobe, individuals with AUD showed less thickness in the fusiform gyrus and lateral occipital gyrus but no difference in the cuneus. 47,49avy alcohol consumption also affected the limbic and subcortical structures.Individuals with AUD showed smaller volume and thickness of the insula and the anterior and posterior cingulate cortex than controls. 47,49,528][49][50][51][52] Counterintuitively, greater alcohol consumption in individuals with AUD was associated with larger cerebellar volume. 48,52

| Sex as a biological variable
Half of the studies included in this review reported on the role of sex as a biological variable in the relationship between alcohol exposure and brain structure (see Table 3).Of the seven studies that included adolescents, the majority reported no moderating effect of sex on structural changes related to alcohol. 25,29,31,34,53One reported a small effect of sex, where females showed a greater decline in volume with increasing age in the supramarginal gyrus. 28Another, from the IMA-GEN sample, found that, among adolescents who initiated heavier drinking, females showed greater atrophy than males. 35For studies of adults with low-to-moderate consumption, most papers found no moderation by sex. 37,39,41,45One study, from the Framingham Offspring Study, showed that alcohol exposure was associated with greater volume loss in females than in males. 36One study was specifically designed to examine sex effects but only found moderation by sex in the cerebellum and amygdala; females showed a greater effect of alcohol towards volume loss in the cerebellum, and males showed a greater effect of alcohol towards volume loss in the amygdala. 48The study found that the effects of alcohol were larger, accounting for 3-9% reductions in volume, but the effects of sex were small and isolated. 48Another study showed that males with AUD, relative to healthy males, showed smaller volumes in the amygdala, but females with AUD did not differ from healthy females. 50Overall, the moderating effect of sex as a biological variable seems limited, but there were some indications that the deleterious effects of alcohol might be greater for female brains, except for the amygdala, which might be more susceptible in males.

| DISCUSSION
This systematic review examined whether alcohol has different effects on brain structure depending on when during the lifespan the exposure or consumption occurs.The studies included in the present review were rated for quality (i.e., statistical rigour and study design), and all but one were determined to be in the highest category.All but one study reported correcting for multiple comparisons (see Table 3).
Evidence from these generally high-quality studies suggests that alcohol consumption leads to similar effects on regional patterns of brain volume in adolescence or adulthood.Further, low and moderate alcohol use showed effects on brain volume in the same direction and same areas as heavy use.Both adolescents and adults who reported heavier alcohol consumption, relative to those who did not, showed reduced frontal and parietal volumes.Alcohol consumption was associated with smaller volumes of the occipital and temporal cortices across developmental stages, but these effects were slightly less consistent.While studies of adults compared volume cross-sectionally, the studies of adolescents often examined both cross-sectional brain structure differences and differences in neurodevelopmental trajectories, such as the slope of change in volume over time.Given that 13 of the 27 studies included in the review statistically controlled for the use of other substances (such as tobacco, which may impact brain structure), we presume that the consistent effects on brain structure that emerged across these studies are attributable to the deleterious effects of alcohol itself, not merely to the concurrent use of other potentially harmful substances.
Some brain areas displayed different patterns by age, including the striatum, insula and cingulate.Specifically, adults with AUD or chronic, low-level alcohol exposure had smaller volumes of these areas, but the effects were inconsistent in adolescents.It is possible that these areas may be sensitive to the chronic effects of alcohol but may be resilient in earlier developmental stages (see Table 4).Relatedly, it should be noted that there are little data on the effect of alcohol on the striatum in early adolescents; thus, suggestions about potential resilience of the striatum in this developmental stage are speculative.
Unlike adolescent and adult exposure, prenatal exposure was associated with larger brain volume and thickness in a sample of 9-to 10-year-olds.However, it is unclear if these effects will persist through later neural development.Adults with foetal alcohol spectrum disorders (FASD) have shown smaller volume in the striatum and other brain regions. 54,55There is also evidence of regionally larger volume and thickness in adults with FASD.However, evidence was limited to a single study drawn from the ABCD sample, and alcohol exposure in the study was relatively low (i.e., participants reported an estimated range of total drinks consumed during pregnancy from 0-90, which is more in line with drinking patterns reported within the general population of pregnant individuals compared to prior studies that have specifically focused on FASD 56 ).Alcohol exposure in the prenatal study was also confounded with sociodemographic variables, such as parental income and education, which also affect brain volume. 27Therefore, more evidence is needed to determine how the effects of prenatal alcohol exposure compare to adolescent or adult consumption.
While past neuroimaging studies often used voxel-wise analytic approaches, recent evidence suggests that examining the brain in anatomically and functionally defined parcels is a more meaningful approach to neuroscientific questions. 57Neighbouring regions can differ in function, cell types, connectivity and topography. 58Parcellation study in humans long relied on post-mortem analysis of architectonics (cell types, densities and distributions), but recent work with resting state functional connectivity has led to parcel boundary maps that align with existing architectonic maps and account for nearly 90% of the homogeneity in brain activation patterns during rest. 59These maps are highly reliable for individuals and generalize to new individuals not used for map development at the group level. 59Although none of the studies in this review applied these boundary maps for analysis of the effects of alcohol, they did use parcels that overlap with the boundary maps and offer some clues to which neural networks may be affected by alcohol.For example, evidence in adolescents and adults for lower volume in the superior and middle frontal gyri suggests impacts on three networks that span that cortical space: the fronto-parietal, dorsal attention and default mode networks.Additionally, across adolescents and adults, the precuneus showed lower volume following alcohol consumption, implying change to the default mode network.This implication is corroborated by evidence that adults with AUD show lower efficiency in default mode network processing relative to controls. 60The patterns of smaller volume and thickness in individuals with heavier, relative to lighter, patterns of drinking suggest disruption to network efficiency that underlies healthy brain function.
These findings should be considered from a lifespan perspective.
Typical brain development is characterized by a complex and timesensitive pattern of neurulation, neuronal proliferation and neural migration in utero, 61 followed by rapid increases in grey and white matter volume and density during early childhood, 62 and a period of cortical thinning during late childhood and adolescence, likely due to synaptic pruning. 5Brain volumes then slowly decline over the course of adulthood, with acceleration after roughly age 70 63 with atrophy particularly pronounced in the frontal and temporal lobes. 64The effect of alcohol exposure or consumption during any of these stages must thus be considered relative to these typical trajectories.shown to occur most quickly in the first month of abstinence and to be fastest among those who show the most alcohol-related volume loss. 66,67erall, results from this systematic review indicate that alcohol affects brain structure similarly across developmental stages.Such structural changes could reflect neuronal loss caused by cellular effects of alcohol exposure, such as oxidative stress that can result from proinflammatory cytokines released in response to alcohol. 8The tissue loss may depend on the amount of duration of alcohol exposure, but studies have estimated that the structural changes have effect sizes in the small to medium range, accounting for 3-9% reductions in volume. 48In fact, the magnitude of the differences in brain volume between individuals with AUD relative to controls is large enough that a trained radiologist can visually observe brain scans and classify whether a person has AUD with 66% accuracy, and machine learning approaches are even more accurate than humans, achieving up to 73% accuracy. 68The loss of brain tissue seems to relate to poorer neurocognitive performance related to heavy alcohol use. 69ese negative effects of alcohol on brain structure and function underscore the need for early, targeted clinical interventions, as well as for treatment approaches tailored to developmental stage.

| Limitations of the literature
One challenge within this literature is the inconsistency in reporting and analysis of brain changes.Some studies used fine-grained parcellations of the brain and did not report on whole brain metrics or larger patterns, while other studies primarily reported on whole brain effects or large parcellations and may have missed smaller effects.The discrepancies between these two approaches present a challenge for drawing inference across studies since it is unclear if the approach affects the results.It would be helpful for studies that use fine grained parcellations to also report whole brain metrics, and vice versa.Further, the variable methods used to quantitate brain morphometrics across studies may also contribute to the variability of findings across studies.The literature also has inconsistencies in how it deals with potential factors that could influence the effects of alcohol, such as biological sex, use of other substances, sociodemographic variables such as education and health status (e.g., diabetes).For example, 13 of the 27 studies included in this review covaried for the use of other substances (such as cigarette smoking, which is known to impact brain structure), but the lack of consideration of other substance use in the other papers is a notable limitation.In addition, health, socioeconomic status, race and ethnicity are all potentially linked and may all moderate the effects of alcohol, so careful consideration will be required to disentangle the effects of each.We acknowledge that it is possible that changes in brain structure among adults with AUD may be related to the potential confounding factors listed above, not simply to greater consumption of alcohol or duration of drinking.Relatedly, when relating volume effects to age, most studies do not correct for duration of drinking.Notably, the UK Biobank included only people with British ancestry, so addressing some of these questions may require new data collection.
An additional limitation is that we confined this review to seven neuroimaging consortium studies (with an alcohol-exposed sample size of at least 100 individuals), and our focus on only these seven consortia may mean that other potentially informative studies were excluded.Also, in this review, only studies that tested the effects of alcohol use on brain volume, cortical thickness or surface area were included, but it is also likely that the reverse is true: that is, that preexisting brain volume (or thickness or surface area) differences may be associated with alcohol use. 70,71While the evidence largely supports that alcohol exposure has a causal role in changing brain volume, this does not negate the possibility that brain volume could influence future alcohol use.
A final important limitation is that papers based on data from a given consortium may have had some overlap in the samples that were included, but the extent of overlap is not possible to determine from the papers.This may be considered a weakness in the methodology, given that the consistency of these findings may have been only studies that included samples of at least 100 alcohol-exposedparticipants from the Framingham Offspring Study, UK Biobank, the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA), the Adolescent Brain Cognitive Development (ABCD) Study, the Enhancing Neuro Imaging Genetics Through Meta-Analysis (ENIGMA) Project, the Imaging and Genetic (IMAGEN) Project and the Human Connectome Project (HCP) were included (see Table Electronic literature searches were conducted through MEDLINE, PubMed, Web of Science and Embase on 16-19 June 2023.The full electronic search strategies for MEDLINE, PubMed, Web of Science and Embase are included in the supporting information.For brevity, in

2. 3 |
Data extraction Two extractors independently extracted the data from each included article using a template the four authors created collaboratively in Covidence.Discrepancies in the extractions were resolved by an independent third reviewer.Information extracted for each article was multi-site study or consortium, study design, participant characteristics (alcohol exposure, inclusion/exclusion criteria, total sample, total alcohol-exposure sample, age range of sample, sex, and race), whether the study reported brain structure differences by sex, results (i.e., was alcohol associated with smaller/larger/no difference in brain volume, and in what areas) and which covariates were included.The main covariates extracted included socioeconomic status, sex, age, race, ethnicity, other substance use, other major psychiatric diagnosis and other medical condition.Results are reported and synthesized in narrative form.A visual depiction of the article selection and data extraction process is shown in Figure 1 (PRISMA flowchart), and information about each study that was included is listed in Table

T A B L E 2
Detailed PICOS criteria.Human data from one of these 7 neuroimaging consortia: ABCD, ENIGMA, Framingham Offspring Study, the Human Connectome Project, IMAGEN, NCANDA, UK Biobank • Alcohol exposed sample of at least N = 100 • Data not from one of the 7 consortia • Alcohol-exposed sample below N = 100 Intervention/Determinant • Alcohol exposure • No low-alcohol-exposure group or no low-using individuals in the sample

Table
1, we present the Embase search (which includes MEDLINE).
Search details: Broad concepts and search terms (Embase).
Comparison• Low-alcohol exposure group or non-drinking group • The comparison group was polysubstance use only • Explored family history/genetic risk as a predictor of brain structure but did not test effects of alcohol use/exposure.
• Compared high alcohol use/exposure group vs. a no/low alcohol use/exposure group (cross-sectional/case-control or cohort design) OR • Alcohol use as a continuous predictor in a regression model, where alcohol use in the sample ranges from low use to higher use (cross-sectional or cohort design) OR • Explore longitudinal changes in brain volume as a function of changes in drinking over time (longitudinal or cohort design)